Google ADK（Agent Development Kit）

An open source AI agent development framework launched by Google for building, evaluating, and deploying complex AI agents.

Google AI application development framework

https://pypi.org/project/google-adk/

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Google ADK (Agent Development Kit) is an open source AI agent development framework launched by Google in April 2025. The framework adopts a code-first development model, allowing developers to directly define agent logic, tools and orchestration processes using Python. As a flexible and modular framework, ADK is optimized for the Gemini and Google ecosystems, but its model-independent nature makes it compatible with multiple large language models. The framework is suitable for building a variety of AI agents from simple tasks to complex workflows, and supports local and cloud deployment.
Google ADK is maintained by Google LLC and was officially released at the Google Cloud Next 2025 conference in Las Vegas on April 9, 2025. The latest version of the framework is 1.31.1, released on April 21, 2026. ADK adopts the Apache Software License 2.0 open source license, and the Python version is required to be 3.10 and above. In an era when AI agent frameworks are flourishing, Google launched ADK to provide developers with a flexible, modular and model-independent agent development kit. The framework applies software engineering development principles to AI agent creation, helping developers build, deploy, and orchestrate AI agents from simple tasks to complex workflows.
The core functions of Google ADK revolve around four aspects. The first is a model-independent architecture design. Although ADK is optimized for Gemini and Google ecosystems, the framework itself is model-independent and supports the integration of multiple large language models. This design allows developers to choose the most appropriate model based on specific needs without being bound by a framework. Second is the rich ecosystem of tools. ADK provides rich tool support such as preset tools, custom functions, OpenAPI specifications, and MCP tools. Developers can integrate various external services and APIs into the agent's workflow to achieve more powerful functions. This open design makes ADK highly scalable and able to adapt to various complex business scenarios. The third is the code-first development model. Unlike other low-code or drag-and-drop agent development frameworks, ADK adopts a code-first development approach, allowing developers to define agent logic, tools and orchestration processes directly in Python. This method is very friendly to engineers who are familiar with software development and can give full play to their programming abilities to implement highly customized agent systems. The fourth is a modular multi-agent system. ADK supports the construction of a multi-agent system, which can combine multiple professional agents to form a flexible hierarchical structure. Each agent can focus on a specific task and work together to complete complex workflows. This design makes the system more maintainable and scalable. In terms of installation and use, ADK provides simple installation commands. The stable version can be installed with one click through `pip install google-adk`, while the development version can obtain the latest features through `pip install git+https://github.com/google/adk-python.git@main`. The framework also provides a wealth of optional expansion packages, including A2A protocol support, community functions, development tools, evaluation tools, etc.
Google ADK is a free open source project licensed under the Apache Software License 2.0. This means that anyone can use the framework for free, and the code can be modified and distributed freely. Google builds a developer ecosystem through ADK and promotes the adoption of its Google Cloud services (including Vertex AI Agent Engine, etc.) to achieve business value. For enterprise users, Google offers paid cloud deployment options, including Cloud Run deployment and Vertex AI Agent Engine. These services provide enterprise-level reliability support and managed services, and are the choice for enterprises pursuing simplified operations and maintenance.
Judging from the user feedback searched, Google ADK has received a positive response from the developer community. Users generally believe that ADK's code-first development model makes agent development controllable and professional, and its rich tool ecosystem provides great flexibility. The design of multi-agent systems is considered a powerful tool for building complex workflows. However, users also raised some issues that need attention. First, the learning curve of ADK may be a bit steep for novices, and they need to be familiar with Python development to use it efficiently. Secondly, although the framework itself is free, deployment to Google Cloud may incur related costs. The third is that the documentation and examples are still being improved, and the documentation for some advanced functions may not be detailed enough.
Google ADK represents an important development direction in the field of AI agent development. After Anthropic's Claude Agent, OpenAI's Agents SDK, Anthropic's Computer Use and other technologies were launched one after another, Google's ADK, as an official framework, provides developers with a standardized agent development solution. From a technical perspective, ADK adopts a modern architectural design and applies software engineering development principles to AI agent creation. The framework supports the A2A (Agent2Agent) protocol, a standardized protocol for communication between agents that is expected to become an industry standard. In addition, ADK also supports integration with various external services and APIs, and has good scalability. In terms of the competitive landscape, ADK’s main competitors include Anthropic’s Claude Agent SDK, OpenAI’s Agents SDK, LangChain, CrewAI and other frameworks. Compared with these frameworks, the advantage of ADK lies in its deep integration with the Google ecosystem and Google's powerful cloud service support.
There is relatively little controversy about Google ADK at the moment. Potential risks mainly include: first, as a relatively new framework, the API may change, and adaptive modification may be required during upgrades; second, dependence on Google Cloud services may bring about a lock-in effect; third, use in China may require special network configuration. From the perspective of technical risks, AI agent technology is still developing rapidly, and the framework is updated and iterated rapidly. Users should pay attention to updating the version in time when using it, and pay attention to the change instructions of the official documentation.
Google ADK is particularly suitable for the following types of user groups. The first is developers who have a certain Python development foundation and hope to build and customize AI agents through code. Secondly, for enterprises that need to build complex workflows, ADK's multi-agent system can effectively organize and manage complex tasks. The third is users of the Google ecosystem, who can take full advantage of the deep integration with Gemini and Vertex AI. For developers who are new to ADK, it is recommended to start with the official examples and gradually become familiar with the core concepts and development models of the framework. You can try building simple single-agent applications first, and then gradually transition to complex multi-agent systems. For projects that require deployment to a production environment, it is recommended to evaluate Google Cloud's deployment options and associated costs in detail. If users need alternatives, they can consider Anthropic's Claude Agent SDK, OpenAI's Agents SDK, LangChain framework or CrewAI framework, etc. Each of these frameworks has its own characteristics, and users can choose the appropriate solution based on specific needs and technology stack.
Google ADK is an open source AI agent development framework launched by Google, which provides developers with a flexible, modular and model-independent agent development solution. The framework adopts a code-first development model, supports a rich tool ecosystem and multi-agent systems, and is suitable for various AI agent construction scenarios from simple tasks to complex workflows. As a framework officially launched by Google, ADK is deeply integrated with the Google ecosystem, while maintaining model-independent features and being compatible with a variety of large language models. For teams and individuals who want to develop professionally in the field of AI agents, ADK is an option worth considering.

User Reviews

TGreen_Max3

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Google's official approach is indeed different. ADK's code structure is very professional and easy to use!

Anna.HartK

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pip install google-adk is a one-click installation. It’s easy to get started. You no longer need to manually configure various environments.

JudeRussell

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Although it is optimized for Gemini, it is very conscientious in that it is model-independent and can be used with other models. Thank you!

Ethan391

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The multi-agent system design is great, complex workflows can be easily handled, and efficiency is maximized.

MariaHarris_66

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The learning curve is a bit steep, you need to be familiar with Python development, and it may not be friendly to novices.

greenmeercat342

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Free frame, what more bike! The prostitution party is ecstatic.

RMurphyZ

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A2A protocol support is a highlight, and communication between agents will be more convenient in the future.

Jean.Chavez_X979

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Deeply integrated with Vertex AI, it is easy to deploy to the cloud and is the first choice for enterprise-level applications.

JerryMoore_s

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The code-first development model is very suitable for programmers and has strong customization capabilities.

萧娜

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The tool ecology is very rich, the preset tools and custom functions are very practical, and the efficiency has been significantly improved.

淡然_10

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The official documentation and examples are very detailed, making it easy to learn quickly and even novices can get started.

JCruz_Pro

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The version is updated frequently and there are often new features. Like it!

realطاهاکریمی_2024

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The only problem is that the documentation is still being improved, and the descriptions of some advanced functions are not detailed enough.

NicoleHernandez_Plus942

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Comparing it with LangChain, ADK is more biased towards the Google ecosystem, each with its own merits.

RaymondBrown88

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OpenAPI specification support is very practical. You can directly import existing APIs and save worry!

Kelly_MorganX

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The modular design is great, the code structure is clear, and subsequent maintenance is easy.

小鱼

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Deployment to Cloud Run is very convenient and has a high degree of automation, which is good news for lazy people.

GCastilloX

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The community is getting more and more active, and there are more and more examples and tutorials, which is great.

GSimmons

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Overall, I am very satisfied. Professional developers create professional frameworks, which is great value for money!

Google ADK（Agent Development Kit）

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